Technical Field
Embodiments of the subject matter disclosed herein generally relate to deriving small-scale maps from a large-scale map or database.
Discussion of the Background
Nowadays, people seldom use printed maps, preferring instead to use various computer displays. Computers have had significant positive impacts on enhancing the quality and quantity of information represented in maps. However, these improvements also pose a challenge because it becomes difficult to meaningfully and clearly visualize all the information.
Any map is characterized by a map scale 1:M, which is a ratio between a unit on the map versus a real life-size M. For example, a 1:10,000 scale means that 1 cm on the map corresponds to 10,000 cm=100 m in real life. In a map, there is a minimum size, below which geographic features cannot be clearly recognized. This is called minimum map unit. All geographic features represented in a map should be greater than the minimum map unit. Items represented on the maps—streets, lakes and rivers, buildings, etc.—are known as geographic features.
Theoretically, all the geographic features (which may be stored in a database) may be represented on a large and detailed enough map (called a “large-scale map” in this document) characterized by an original scale 1:Mo. However, in practice, people frequently need maps with small scales (i.e., less detailed) than the original scale. Simplistically, one may think that a small-scale map (characterized by a smaller scale than the original scale) is merely a proportionally smaller version of the large-scale map. However, such a proportional approach sabotages the ability to distinguish the geographic features, rendering the proportional small-scale map useless; see FIG. 8 for an illustration.
Conventionally, operator intervention has been employed to derive small-scale maps of a few limited scales rather than all scales, yet even when assisted by software tools, it is a subjective and time-consuming approach. Research has been carried out to derive a few limited scales of maps that involve often some geographic features rather than all geographic features. Overall, there is no automatic solution to map generation of small scales, so in practice multiple scales of maps and databases are maintained. Thus it creates enormous difficulties to maintain and update these maps and databases.
Another drawback in the conventional approach to generating maps with scales smaller than an original scale is that it is done step by step, with each map being obtained from its closest larger scale map. This step-by-step approach can propagate errors from one map to the next.
Therefore, it is desirable to develop automated methods that avoid maintaining and updating multiple scales of maps or databases, and avoid the drawbacks of the conventional approach.